Sort by match of LIKE

Since all your matches have to match the LIKE pattern in order to be included, the simple thing to do is assume that shorter values for the column you're matching are "better" matches, as they're closer to the exact value of the pattern.

ORDER BY LEN(item_nale) ASC

Alternatively, you could assume that values in which the match pattern appear earlier are "better" matches.

ORDER BY PATINDEX('%' + @user_input + '%', item_nale) ASC

Or you could combine the two; look for earliest matches first, and within those, prefer shorter values.

ORDER BY PATINDEX('%' + @user_input + '%', item_nale) ASC, LEN(item_nale) ASC

It's not as sophisticated as what full-text indexing does, and it only accounts for matching on a single column, but it gives decent enough results.

It isn't possible to calculate relevance with the LIKE predicate. For SQL Server (which from previous questions I believe is your platform?) you'll want to look at full-text search which supports scoring/ranking results by relevance.

Generate the Levenshtein function, and order by this field.

Ref: https://www.red-gate.com/simple-talk/blogs/string-comparisons-in-sql-edit-distance-and-the-levenshtein-algorithm/

If you have this function, it could be:

select 
   field1,
   field2,
   field3,
   fieldN,
   item_nale,
   MyLevenshteinFunction(item_nale,@user_input) LevenshteinDistance
from (
    select 
       field1,
       field2,
       field3,
       fieldN,
       item_nale,
       LevenshteinDistance
    from
    articles
    where item_nale like '%'+@user_input +'%'
) as result
order by LevenshteinDistance DESC